CrosSing: A framework to develop knowledge-based recommenders in cross domains M AZAK – 2010 – etd.lib.metu.edu.tr Page 1. CROSSING: A FRAMEWORK TO DEVELOP KNOWLEDGE-BASED RECOMMENDERS IN CROSS DOMAINS A THESIS SUBMITTED TO THE GRADUATE SCHOOL OF NATURAL AND APPLIED SCIENCES OF MIDDLE EAST TECHNICAL UNIVERSITY BY … Cited by 4 Related articles All 2 versions

Evaluating the effectiveness of personalised recommender systems in learning networks H Drachsler, H Hummel, B van den Berg… – … Network Services for …, 2009 – Springer … On the framework side you can choose between three different recommender systems the Taste, the CoFE, and the Duine framework. … Finally, the Duine (http://sourceforge.net/projects/duine/) framework allows users to develop own prediction engines for recommender systems. … Cited by 4 Related articles All 5 versions

Recommendation of Television Programs AP Lucas – fenix.tecnico.ulisboa.pt … To evaluate the various techniques, I developed a prototype recommendation system using the Duine Framework [29]. In order to compare the studied techniques, I began by collecting and statistically defining a test data set, given that no specific standard data set Page 2. … Related articles

The Architecture and Datasets of Docear’s Research Paper Recommender System S Langer, B Gipp – Under Review at RecSys2014. Pre-print available at …, 2014 – docear.org … Some of them are LensKit, Recommender101, EasyRec, Crab, Mahout, MyMediaLite, RecLab, R-Forge, and the Duine Framework. 3. INTRODUCTION TO DOCEAR Docear is an open source literature suite for organizing references and PDFs. … Cited by 3 Related articles

A framework for the rapid prototyping of knowledgebased recommender systems in the learning domain A Ruiz-Iniesta, G Jiménez-Díaz… – Journal of Research …, 2012 – search.informit.com.au … Nowadays, there exist some libraries that help in the development of recommender systems, for example: Mahout1, Duine2, MyMediaLite 1 http://mahout.apache.org/ 2 http://www. duineframework.org/ Page 3. Journal of Research and Practice in Information Technology, Vol. … Cited by 2 Related articles All 12 versions

Enhancing Accuracy of Hybrid Recommender Systems through Adapting the Domain Trends F Aksel, A Birtürk – Workshop on the Practical Use of …, 2010 – etd.lib.metu.edu.tr … vision that sparked the writing of this thesis. I would like to thank Mark van Setten and the creators of the Duine Framework for producing a high quality piece of software and making it open-source. … 14 Table 2.2 Duine Framework Prediction Techniques . . . . . … Cited by 2 Related articles All 8 versions

Prea: Personalized recommendation algorithms toolkit J Lee, M Sun, G Lebanon – The Journal of Machine Learning Research, 2012 – dl.acm.org … 3. Details can be found at https://cwiki.apache.org/confluence/display/MAHOUT/. 4. Details can be found at http://taste.sourceforge.net/old.html. 5. Details can be found at http://www. duineframework.org/. 6. Details can be found at http://www.nongnu.org/cofi/. … Cited by 3 Related articles All 6 versions

Comparison of group recommendation algorithms T De Pessemier, S Dooms, L Martens – Multimedia Tools and Applications, 2013 – Springer … of the content items. As a content-based solution, the Inter- estLMS predictor of the open source implementation of the Duine framework [31] is adopted (and extended to consider extra metadata attributes). Based on the metadata … Cited by 2 Related articles

Universal Recommender System P Cvengroš, P Cvengroš – 2011 – unresyst.googlecode.com … listened yesterday. In our notation: ˆuR(Bob, Beck) = (0.8,“Bob has listened to Sonic Youth band, which is similar to Beck”). Our expectancy concept is similar to the one used in the Duine framework [16]. The prediction techniques … Cited by 1 Related articles All 2 versions